Ben Shababo: May 1st


Title: Optimal Sequential Stimulation of Neural Populations For Inferring Functional Connectivity

Abstract: In this talk, we will review ongoing work in which we use methods from Bayesian experimental design, a subset of Active Learning, to guide an circuit mapping experiment. Specifically, the experimental paradigm we assume includes the recording of some output from a single cell - such as membrane voltage or current - and the ability to stimulate some subset of nearby neurons. The goal of the experiment is to learn the vector of weights that describe the influence of the cells we can stimulate on the cell we are recording from. In Bayesian experimental design the objective is to maximize the mutual information between the data and the parameters one wishes to learn which in turn entails a probabilistic model. For our model, we use a spike-and-slab prior on the weights with a linear gaussian likelihood. Furthermore, since this algorithm must perform in an online setting, we speed up the algorithm by approximating the optimization with a greedy version of the algorithm and by using online Bayesian updating of the posterior during stimulus selection. We will present results that show that within a specific regime our procedure outperforms random stimulation. We will also present some ideas we are currently incorporating into our model to make it more robust and applicable for the current state of experimental technology.

David Greenberg: April 24th 

Title: Accurate Optical AP Detection During ‘Natural’ Behavior: Two Inference Problems

Abstract: Two-photon calcium imaging can detect single action potentials in populations of spatially resolved neurons in vivo, but using it to quantitatively compare spiking and behavior requires solving several problems of analysis and experimental technique. This talk will focus on two such problems: accurately inferring spike counts from fluorescence signals, and measuring visual input in freely moving animals. For optical action potentials detection several algorithms exist along with a growing corpus of ground truth datasets. I will describe these as well as some current work to develop algorithms that are effective on a wide range of in vivo data, to develop metrics for testing spike inference, and to create a public database of ground truth measurements. In the second half of my talk, I will describe a system for eye tracking in freely moving rats compatible with two-photon imaging through optical fibers. I will also briefly describe some insights into the activity of cortical populations and rodent visual behavior provided by these methods.

Kamiar Rahnama Rad: April 17th

Title: A simple proof for the Marchenko-Pastur law

Abstract: I review the proof of the Wigner semicircle law for Wigner matrices using the Stieltjes transform method described here. Using this method, I will present a new simple proof to the old Marchenko-Pastur law, which describes the asymptotic behavior of singular values of large sample covariance matrices.

Attila Losonczy: April 10th 

Title: Functional imaging hippocampal microcircuits in behaving mice.

Abstract: I my talk I will introduce recently developed methods for functional two-photon imaging genetically and anatomically-defined cellular and subcellular components of the hippocampal CA1 microcircuit in awake behaving  mice. I will review some advantages of this approach as well as current experimental and analytical challenges to dissect the role of identified presynaptic and postsynaptic circuit motifs in hippocampal memory behaviors.

Eftychios Pnevmatikakis: April 3rd

Title: A brief introduction to determinantal point processes

Abstract: a brief introduction to determinantal point processes, a class of probabilistic models that model global negative interactions, yet allow for tractable inference. Material will be drawn from http://arxiv.org/abs/1207.6083  from (chapters 1-4). Time permitting, we will also discuss the approach of this paper: http://books.nips.cc/papers/files/nips25/NIPS2012_1357.pdf